Early Detection of Wild Rocket Tracheofusariosis Using Hyperspectral Image-Based Machine Learning

Fusarium oxysporum f. sp. raphani is responsible for wilting wild rocket (Diplotaxis tenuifolia L. [D.C.]). A machine learning model based on hyperspectral data was constructed to monitor disease progression. Thus, pathogenesis after artificial inoculation was monitored over a 15-day period by symptom assessment, qPCR pathogen quantification, and hyperspectral imaging. The host colonization by a pathogen evolved accordingly with symptoms as confirmed by qPCR. Spectral data showed differences as early as 5-day post infection and 12 hypespectral vegetation indices were selected to follow disease development. The hyperspectral dataset was used to feed the XGBoost machine learning algorithm with the aim of developing a model that discriminates between healthy and infected plants during the time. The multiple cross-prediction strategy of the pixel-level models was able to detect hyperspectral disease profiles with an average accuracy of 0.8. For healthy pixel detection, the mean Precision value was 0.78, the Recall was 0.88, and the F1 Score was 0.82. For infected pixel detection, the average evaluation metrics were Precision: 0.73, Recall: 0.57, and F1 Score: 0.63. Machine learning paves the way for automatic early detection of infected plants, even a few days after infection

A preliminary study on metabolome profiles of buffalo milk and corresponding mozzarella cheese: Safeguarding the authenticity and traceability of protected status buffalo dairy products

The aim of this study is to combine advanced GC-MS and metabolite identification in a robust and repeatable technology platform to characterize the metabolome of buffalo milk and mozzarella cheese. The study utilized eleven dairies located in a protected designation of origin (PDO) region and nine dairies located in non-PDO region in Italy. Samples of raw milk (100 mL) and mozzarella cheese (100 g) were obtained from each dairy. A total of 185 metabolites were consistently detected in both milk and mozzarella cheese. The PLS-DA score plots clearly differentiated PDO and non-PDO milk and mozzarella samples. For milk samples, it was possible to divide metabolites into two classes according to region: those with lower concentrations in PDO samples (galactopyranoside, hydroxybuthyric acid, allose, citric acid) and those with lower concentrations in non-PDO samples (talopyranose, pantothenic acid, mannobiose, etc.,). The same was observed for mozzarella samples with the proportion of some metabolites (talopyranose, 2, 3-dihydroxypropyl icosanoate, etc.,) higher in PDO samples while others (tagatose, lactic acid dimer, ribitol, etc.,) higher in non-PDO samples. The findings establish the utility of GC-MS together with mass spectral libraries as a powerful technology platform to determine the authenticity, and create market protection, for “Mozzarella di Bufala Campana.

Metastatic mixed gestational trophoblastic tumour of the uterus: A case report

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Emergency transapical mitral valve-in-valve implantation for bioprosthesis failure: Transapical implantation of an Edwards Sapien-XT in a dysfunctional mitral bioprosthesis in a critical patient

Background: Valve-in-Valve (VIV) Transcatheter Aortic Valve Replacement (TAVR) is now the treatment of choice in high-surgical-risk patients with failing aortic bioprosthesis. Although less performed, VIV-Transcatheter Mitral Valve Replacement (TMVR) is a valid treatment option for selected high-risk patients with degenerated mitral bioprostheses. Several cases of elective ViV- TAVR and -TMVR have been reported but only few were performed in critical hemodynamic conditions. Case presentation: We report the case of a patient underwent balloon-expandable transapical mitral valve-in-valve implantation in an emergency setting due to a severe stenosis of a bioprosthesis in mitral position. The procedure was successfully performed, with no residual mitral regurgitation or paravalvular leaks, and uneventful. Conclusion: Transcatheter transapical mitral valve-in-valve implantation could represent a feasible and effective strategy even in critical setting

Plant Dynamic Metabolic Response to Bacteriophage Treatment After Xanthomonas campestris pv. campestris Infection

Periodic epidemics of black rot disease occur worldwide causing substantial yield losses. Xanthomonas campestris pv. campestris (Xcc) represents one of the most common bacteria able to cause the above disease in cruciferous plants such as broccoli, cabbage, cauliflower, and Arabidopsis thaliana. In agriculture, several strategies are being developed to contain the Xanthomonas infection. The use of bacteriophages could represent a valid and efficient approach to overcome this widespread phenomenon. Several studies have highlighted the potential usefulness of implementing phage therapy to control plant diseases as well as Xcc infection. In the present study, we characterized the effect of a lytic phage on the plant Brassica oleracea var. gongylodes infected with Xcc and, for the first time, the correlated plant metabolic response. The results highlighted the potential benefits of bacteriophages: reduction of bacterium proliferation, alteration of the biofilm structure and/or modulation of the plant metabolism and defense response

An Algebraic Approach for Decoding Spread Codes

In this paper we study spread codes: a family of constant-dimension codes for random linear network coding. In other words, the codewords are full-rank matrices of size (k x n) with entries in a finite field F_q. Spread codes are a family of optimal codes with maximal minimum distance. We give a minimum-distance decoding algorithm which requires O((n-k)k^3) operations over an extension field F_{q^k}. Our algorithm is more efficient than the previous ones in the literature, when the dimension k of the codewords is small with respect to n. The decoding algorithm takes advantage of the algebraic structure of the code, and it uses original results on minors of a matrix and on the factorization of polynomials over finite fields

A multi-model assessment of the impact of currents, waves and wind in modelling surface drifters and oil spill

Validation of oil spill forecasting systems suffers from a lack of data due to the scarcity of oil slick in situ and satellite observations. Drifters (surface drifting buoys) are often considered as proxy for oil spill to overcome this problem. However, they can have different designs and consequently behave in a different way at sea, making it not straightforward to use them for oil spill model validation purposes and to account for surface currents, waves and wind when modelling them. Stemming from the need to validate the MEDESS4MS (Mediterranean Decision Support System for Marine Safety) multi-model oil spill prediction system, which allows access to several ocean, wave and meteorological operational model forecasts, an exercise at sea was carried out to collect a consistent dataset of oil slick satellite observations, in situ data and trajectories of different type of drifters. The exercise, called MEDESS4MS Serious Game 1 (SG1), took place in the Elba Island region (Western Mediterranean Sea) during May 2014. Satellite images covering the MEDESS4MS SG1 exercise area were acquired every day and, in the case an oil spill was observed from satellite, vessels of the Italian Coast Guard (ITCG) were sent in situ to confirm the presence of the pollution. During the exercise one oil slick was found in situ and drifters, with different water-following characteristics, were effectively deployed into the oil slick and then monitored in the following days. Although it was not possible to compare the oil slick and drifter trajectories due to a lack of satellite observations of the same oil slick in the following days, the oil slick observations in situ and drifters trajectories were used to evaluate the quality of MEDESS4MS multi-model currents, waves and winds by using the MEDSLIK-II oil spill model. The response of the drifters to surface ocean currents, different Stokes drift parameterizations and wind drag has been examined. We found that the surface ocean currents mainly drive the transport of completely submerged drifters. The accuracy of the simulations increases with higher resolution currents and with addition of the Stokes drift, which is better estimated when provided by wave models. The wind drag improves the modelling of drifter trajectories only in the case of partially emerged drifters, otherwise it leads to an incorrect reproduction of the drifters׳ direction, which is particularly evident in high speed wind conditions

Phosphodiesterase 3B Is Localized in Caveolae and Smooth ER in Mouse Hepatocytes and Is Important in the Regulation of Glucose and Lipid Metabolism

Cyclic nucleotide phosphodiesterases (PDEs) are important regulators of signal transduction processes mediated by cAMP and cGMP. One PDE family member, PDE3B, plays an important role in the regulation of a variety of metabolic processes such as lipolysis and insulin secretion. In this study, the cellular localization and the role of PDE3B in the regulation of triglyceride, cholesterol and glucose metabolism in hepatocytes were investigated. PDE3B was identified in caveolae, specific regions in the plasma membrane, and smooth endoplasmic reticulum. In caveolin-1 knock out mice, which lack caveolae, the amount of PDE3B protein and activity were reduced indicating a role of caveolin-1/caveolae in the stabilization of enzyme protein. Hepatocytes from PDE3B knock out mice displayed increased glucose, triglyceride and cholesterol levels, which was associated with increased expression of gluconeogenic and lipogenic genes/enzymes including, phosphoenolpyruvate carboxykinase, peroxisome proliferator-activated receptor γ, sterol regulatory element-binding protein 1c and hydroxyl-3-methylglutaryl coenzyme A reductase. In conclusion, hepatocyte PDE3B is localized in caveolae and smooth endoplasmic reticulum and plays important roles in the regulation of glucose, triglyceride and cholesterol metabolism. Dysregulation of PDE3B could have a role in the development of fatty liver, a condition highly relevant in the context of type 2 diabetes